Initial read_parquet MVP implementation

src/nested_pandas/nestedframe/__init__.py

@@ -1 +1,2 @@
 from .core import NestedFrame  # noqa
+from .io import read_parquet  # noqa

src/nested_pandas/nestedframe/io.py

@@ -0,0 +1,69 @@
+# typing.Self and "|" union syntax don't exist in Python 3.9
+from __future__ import annotations
+
+import pandas as pd
+
+from .core import NestedFrame
+
+
+def read_parquet(
+    data: str,
+    to_pack: dict,
+    engine: str = "auto",
+    columns: list[str] | None = None,
+    pack_columns: dict | None = None,
+) -> NestedFrame:
+    """
+    Load a parquet object from a file path and load a set of other
+    parquet objects to pack into the resulting NestedFrame.
+
+    Docstring based on the Pandas equivalent.
+
+    #TODO after MVP: Include full kwarg-set
+
+    Parameters
+    ----------
+    data : str, path object or file-like object
+        String, path object (implementing ``os.PathLike[str]``), or file-like
+        object implementing a binary ``read()`` function.
+        The string could be a URL. Valid URL schemes include http, ftp, s3,
+        gs, and file. For file URLs, a host is expected. A local file could be:
+        ``file://localhost/path/to/table.parquet``.
+        A file URL can also be a path to a directory that contains multiple
+        partitioned parquet files. Both pyarrow and fastparquet support
+        paths to directories as well as file URLs. A directory path could be:
+        ``file://localhost/path/to/tables`` or ``s3://bucket/partition_dir``.
+    to_pack: dict,
+        A dictionary of parquet data paths (same criteria as `data`), where
+        each key reflects the desired column name to pack the data into and
+        each value reflects the parquet data to pack.
+    engine : {{'auto', 'pyarrow', 'fastparquet'}}, default 'auto'
+        Parquet library to use. If 'auto', then the option
+        ``io.parquet.engine`` is used. The default ``io.parquet.engine``
+        behavior is to try 'pyarrow', falling back to 'fastparquet' if
+        'pyarrow' is unavailable.
+
+        When using the ``'pyarrow'`` engine and no storage options are provided
+        and a filesystem is implemented by both ``pyarrow.fs`` and ``fsspec``
+        (e.g. "s3://"), then the ``pyarrow.fs`` filesystem is attempted first.
+        Use the filesystem keyword with an instantiated fsspec filesystem
+        if you wish to use its implementation.
+    columns : list, default=None
+        If not None, only these columns will be read from the file.
+    pack_columns: dict, default=None
+        If not None, selects a set of columns from each keyed nested parquet
+        object to read from the nested files.
+
+    Returns
+    -------
+    NestedFrame
+    """
+
+    df = NestedFrame(pd.read_parquet(data, engine, columns))
+
+    for pack_key in to_pack:
+        col_subset = pack_columns[pack_key] if pack_columns is not None else None
+        packed = pd.read_parquet(to_pack[pack_key], engine=engine, columns=col_subset)
+        df = df.add_nested(packed, pack_key)
+
+    return df